2026-03-21 22:02:45
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Today at a glance:
🇨🇳 Alibaba: $100 Billion AI Bet
🌐 Accenture: AI Transition Continues
🚚 FedEx: Efficiency Over Expansion
🍪 General Mills: Reinvestment Pains
🫒 Darden: Strategic Shifts
🚖 Didi: Cost of Conquest
🧘🏻 Lululemon: Global Tug-of-War
✍️ DocuSign: Billings Hit $1 Billion
🏥 HealthEquity: Asset & Margin Records
🌎 dLocal: $1 Billion Milestone
Alibaba’s Q3 FY26 (December quarter) saw revenue rise 2% Y/Y to $40.7 billion ($1.4 billion miss), though like-for-like growth (excluding exited businesses like Sun Art and Intime) was a more robust 9%.
The headline story was a 67% plunge in adjusted net income, as the company doubled down on its investment phase. This aggressive spending centers on three areas: quick-commerce subsidies, user experience, and a massive build-out of AI infrastructure.
The company is effectively cannibalizing short-term retail profits to fund a full-stack AI future:
Cloud Intelligence Group: Revenue growth accelerated to 36% Y/Y, with AI-related product revenue posting its tenth consecutive quarter of triple-digit growth. CEO Eddie Wu set a bold new target to reach $100 billion in annual Cloud and AI revenue within five years. To accelerate monetization, Alibaba recently hiked prices for cloud and storage services by up to 34%.
T-Head & Token Hub: Alibaba is vertically integrating its AI via its proprietary chip unit, T-Head, which has now shipped over 470,000 AI chips. The newly formed Alibaba Token Hub (ATH) group consolidates all AI units under Eddie Wu to streamline the adoption of “Model-as-a-Service” (MaaS).
China E-commerce & Quick Commerce: While core e-commerce revenue grew 6%, the Quick Commerce segment surged 56% to ~$3 billion. This business is currently a loss leader used to defend market share against Meituan and JD.com, with a goal of hitting RMB 1 trillion in Gross Merchandise Value (~$143 billion) by FY28.
The quarter included significant headwinds. The surprise departure of Junyang Lin, a lead Qwen developer, raised questions about research continuity. In addition, while the Qwen App surpassed 300 million MAUs, the rise of agentic AI has given Tencent’s Weixin/WeChat ecosystem an early advantage.
Alibaba’s management characterized the current profit dip as a deliberate choice. They project that the Quick Commerce segment will turn profitable by FY29 and that the integration of T-Head chips will enable “non-linear leaps” in cloud profitability by reducing reliance on expensive external silicon.
2026-03-20 20:03:57
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Capital is shifting aggressively toward chips, data centers, and model infrastructure. At the same time, management teams are openly questioning how much human labor their future operations actually require.
ServiceNow CEO Bill McDermott recently warned that AI agents could push unemployment for new college graduates into the mid-30% range within two years. While that prediction sounds extreme, the broader shift is already manifesting in corporate behavior.
This week offered three very different examples of that shift.
Today at a glance:
🤖 Meta: More Chips Fewer Humans
📱 Tencent: Agents Meet Distribution
☁️ Micron: Demand Goes Vertical
Meta’s massive AI CapEx ramp continues to materialize, one infrastructure deal after another.
This week, the company signed a deal worth up to $27 billion over five years with AI cloud provider Nebius, including $12 billion of dedicated capacity starting in early 2027. It is another reminder that Zuck is racing to lock in as much compute as possible before capacity tightens further.
At the same time, Reuters reported that Meta is considering layoffs that could affect 20% or more of its workforce, though the company pushed back, calling the report speculative. If it happens, it would be Meta’s biggest cut since the ‘year of efficiency’ layoffs in 2023.
The two headlines are connected. Meta is not slowing its AI spending. It is reallocating. The company wants more data centers, more chips, and fewer workers doing jobs that AI can increasingly automate. Reuters noted that analysts estimate cuts of that size could save roughly $6 billion. That barely moves the needle for a company planning ~$125 billion in 2026 CapEx.
The bigger picture is that Meta is starting to look like the clearest example of what the AI era may do to Big Tech cost structures. The new org chart may be built less around adding headcount and more around adding compute.
Tencent’s core business is strong enough to fund a much more aggressive AI push. Q4 revenue rose 13% Y/Y to RMB 194 billion (~$28 billion), while net profit climbed 15%, helped by the higher-margin mix shift toward gaming and advertising.
Gaming led the quarter: Overseas gaming revenue surged 32% to RMB 21.1 billion in Q4. Success was driven by Supercell’s recovery (notably Clash Royale) and the breakout hit Delta Force. Meanwhile, China gaming revenue grew 15% to RMB 38.2 billion, supported by evergreen titles and the launch of Valorant Mobile.
Ad tech is scaling efficiently: Marketing services rose 17% to RMB 41.1 billion. Tencent said its AiM Plus ad model uses generative AI to create and target content, helping the business outgrow the broader Chinese advertising market.
Tencent’s previously measured AI posture is giving way to a much more aggressive one. The company now plans to double AI investment to over RMB 36 billion in 2026 (~$5 billion), funded in part by reduced share buybacks. That push also includes a major Hunyuan 3.0 upgrade expected in April, backed by a restructured research team.
Agents inside the super app: Tencent is moving beyond chatbots to agentic AI. It recently launched QClaw (an AI assistant integrated into WeChat) and WorkBuddy, leveraging the viral OpenClaw framework to automate tasks like travel booking and ride-hailing for its 1.42 billion MAUs.
Cloud is becoming a profit engine: Business Services generated a record RMB 5 billion in adjusted operating profit for the year, showing that Tencent’s pivot toward higher-quality PaaS and SaaS is working.
GPU supply constraints held back hardware purchases in Q4, but Tencent expects that to change in 2026 as H200 chips become more available. The bigger takeaway is that Tencent now has the cash flow, distribution, and product surface area to turn AI from an experiment into a real platform advantage.
Micron just released its Q2 FY26 earnings (February quarter), and the results suggest this cycle is accelerating faster than even bullish investors expected. While the stock dipped on aggressive spending plans, the underlying fundamentals remain extraordinary.
Revenue for Q2 skyrocketed 196% Y/Y to $23.9 billion, beating consensus by over $4.5 billion. To put that in perspective, Micron’s revenue guidance for the next quarter alone (~$33.5 billion) now exceeds the full-year revenue of every year in the company’s history through 2024.
Gross margins hit 74%, up from 56% just three months ago. Micron’s guidance for the next quarter points to an 81% gross margin, a figure that actually edges out NVIDIA’s current levels.
So, why did the stock slide? The answer lies in the massive capital requirements to stay on top.
CapEx surge: Micron raised its FY26 CapEx forecast to over $25 billion, up from the $20 billion discussed last quarter.
2027 ramp: Management warned that fiscal 2027 spending will “step up meaningfully,” increasing by more than $10 billion over 2026 levels.
The investor dilemma: Revenue is booming, but some investors are uneasy about how much cash Micron must pour into fabs in Idaho and New York to keep up.
The memory shortage has evolved beyond an AI-only narrative. It is now rippling through the broader electronics ecosystem.
HBM4 momentum: Micron has begun volume shipments of HBM4 for NVIDIA’s next-generation platforms, securing its position in a market many feared it would lose to SK Hynix and Samsung.
A longer shortage? While analysts once hoped supply would normalize by 2027, some industry leaders now think tightness could persist for four to five more years.
Consumer spillover: HP recently said memory prices roughly doubled in a single quarter. As Micron prioritizes high-margin AI memory, standard PC and phone manufacturers are fighting for scraps, driving hardware costs higher for everyone.
NVIDIA’s Vera Rubin allocation: The next major catalyst is the volume of HBM4 orders for NVIDIA’s upcoming Vera Rubin line. Any shift in how NVIDIA allocates these orders between the Big Three (Micron, Samsung, SK Hynix) will move the needle significantly.
Margin ceiling: With gross margin guidance at 81%, the market will be watching to see whether Micron is nearing a ceiling for profitability or whether pricing power can push margins even higher.
For now, Micron is one of the primary beneficiaries of AI’s second-order effects. Training and inference need compute, compute needs memory, and the world still cannot build enough of it. The open question is no longer whether the demand is real, but how long supply can remain this far behind it.
That's it for today.
Happy investing!
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Disclosure: I own META and TCEHY in App Economy Portfolio. I share my ratings (BUY, SELL, or HOLD) with App Economy Portfolio members.
Author's Note (Bertrand here 👋🏼): The views and opinions expressed in this newsletter are solely my own and should not be considered financial advice or any other organization's views.
2026-03-17 20:03:12
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“The inference inflection has arrived.”
That was Jensen Huang’s message at NVIDIA’s annual GTC keynote on Monday.
The company came into the event with something to prove. NVIDIA is already worth more than $4.4 trillion, but the stock had been under pressure this year as investors looked for evidence that the AI boom was still expanding. Huang’s answer? NVIDIA now sees at least $1 trillion of AI chip revenue opportunity through 2027.
But that number comes with an important catch.
This is not a new annual revenue guide. It is a cumulative platform forecast extending the old $500 billion through 2026 outlook by one more year. In other words, the message from GTC was less about a sudden new explosion in near-term sales and more about something arguably more important. NVIDIA is trying to prove that the next phase of the AI race will be defined by inference, agentic workloads, and the full AI factory. And the company intends to own all three.
Let’s cover in plain English the four key takeaways and what they imply for NVIDIA’s outlook, the broader AI trade, and the public companies tied to it.
Today at a glance:
A trillion-dollar outlook with a catch
Inference is the new battlefield
The moat moves up the stack
Winners and losers from GTC
2026-03-14 22:00:41
Welcome to the Saturday PRO edition of How They Make Money.
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📊 Monthly reports: 200+ companies visualized.
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Today at a glance:
🛢️ Aramco: Geopolitical Storms
🖥️ HPE: Networking Takes the Wheel
🔷 Rubrik: Mission Control for the AI Era
🤖 UiPath: Growth Ceiling
👁️ SentinelOne: New Leadership
⚡️ NIO: Profit Inflection Point
🎿 Vail Resorts: Worst-Case Winter
Saudi Aramco is operating at the center of a global energy crisis. While the financial headlines from its annual report show a slight retreat in profit and revenue, the narrative is dominated by the company’s response to the Iran war and the strategic blockade of the Strait of Hormuz.
Despite the extreme volatility in the Middle East, Aramco maintained a high level of profitability, though it cooled slightly from the record-breaking previous years:
Profit & revenue: Full-year net income dipped to $93.4 billion (down from $106.2 billion in 2024). Total revenue fell 7% Y/Y to $445.7 billion, primarily due to lower average crude prices, which hit $64.10/bbl in Q4.
Shareholder returns: In a historic move, Aramco announced its first-ever $3 billion share buyback program. It also raised its Q4 base dividend by 3.5% to $21.9 billion, marking the fourth consecutive year of dividend growth.
Capital investment: The company executed a massive $52.2 billion capital program. Looking ahead to 2026, spending is expected to peak between $50 billion and $55 billion as it invests in liquids-to-chemicals and new energy.
The regional military escalations forced Aramco into an emergency logistical shift. With the Strait of Hormuz blocked, CEO Amin Nasser warned of “catastrophic consequences” for the global economy if shipping does not resume.
The East-West lifeline: To bypass the blockade, Aramco is rerouting its Arab Light and Extra Light grades via the East-West pipeline to the Yanbu port on the Red Sea. This route reached its full 7 million bpd capacity on March 11.
Production cuts: Because the pipeline cannot handle Aramco’s full export volume, the company has reduced output by 2 million bpd. According to the International Energy Agency (IEA), this is the largest oil supply disruption in history, with roughly 10 million bpd of regional production currently offline.
Refinery recovery: The giant Ras Tanura refining complex, the largest in the kingdom, successfully restarted operations on March 10. While it is currently operating at limited capacity, the facility has recovered from the drone attacks that occurred earlier this month.
While the IEA has authorized a record 400 million barrel reserve release to cap prices, analysts warn this is only a temporary bridge. With Brent crude swinging back near $100 per barrel and tanker insurance rates soaring, the market is grappling with a physical shortage. The coming weeks will determine if the global economy can absorb these costs or if the persistent blockade will trigger a more severe inflationary crisis.
2026-03-13 20:02:08
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Today at a glance:
🎨 Adobe: AI Scare Trade
🎟️ Live Nation: Keeping Ticketmaster
🤖 Meta: Going Deeper Into Custom AI Chips
Adobe’s Q1 2026 results came with the end of an era.
The architect of Adobe’s cloud transformation, CEO Shantanu Narayen plans to step down after 18 years. Despite beating estimates across the board, shares fell about 7% as investors weighed leadership uncertainty and persistent fears around AI disruption.
Adobe’s AI strategy is starting to show up in the numbers:
Double beat: Revenue grew 12% Y/Y to $6.4 billion ($120 million beat). Non-GAAP EPS reached $6.06, well above the $5.87 expected.
Strong user growth: Monthly active users reached 850 million (+17% Y/Y). Creative Premium MAU surged 50%, fueled by the freemium funnel for Express and Firefly.
Cash powerhouse: Adobe generated nearly $3 billion in operating cash flow and maintained a sky-high non-GAAP operating margin of 47%.
Next billion-dollar business: ARR from AI-first applications such as Firefly for Enterprise more than tripled Y/Y. Firefly ARR has already crossed $250 million, and Narayen called it Adobe’s next billion-dollar pillar. Still, it remains a tiny portion of total ARR, which grew 11% to $26.1 billion.
The CEO transition follows a similar move at Workday, where the CEO recently stepped aside for a founder-led AI pivot. Narayen will remain as Chair of the Board and CEO until a successor is found. The timing of the exit is curious, given that the board recently approved a new long-term performance share program for Narayen that doesn't vest until early 2029.
This transition comes at a delicate time for the company. AI is a growth engine, but it is also a double-edged sword. Adobe said its traditional stock business, which generates $450 million a year, is declining faster than expected as users shift to generative AI alternatives. This shift captures the core SaaSpocalypse anxiety. The company is successfully selling AI tools, but those tools are also cannibalizing its own high-margin legacy segments.
Adobe is betting its 850 million user base will eventually graduate into paid tiers as they hit AI paywalls for advanced generative features. Q2 guidance was ahead of Wall Street estimates, targeting revenue of $6.43-$6.48 billion, but it still implies a slowdown (+9-10% Y/Y). For a company trying to prove AI can bring reacceleration, single-digit growth is nothing to write home about.
The market remains deeply skeptical, with shares down nearly 30% so far in 2026. At less than 12x forward earnings, Adobe is no longer priced like a premium software franchise. The challenge for the next CEO is straightforward: prove Adobe can turn its AI funnel into durable monetization before rivals and AI-native tools reshape the category around it.
The long-running antitrust battle over Live Nation and Ticketmaster took a surprising turn this week.
The US Department of Justice (DOJ) reached a settlement with Live Nation, allowing the company to keep Ticketmaster and avoid the structural breakup regulators had initially pursued. Importantly, the deal does not include a federal financial penalty.
Instead, the agreement focuses on operational concessions designed to increase competition:
Ticketmaster must allow venues to sell up to 50% of tickets through rival marketplaces.
Service fees at Live Nation-controlled venues will be capped at 15%.
The company must terminate exclusive ticketing agreements at 13 amphitheaters and offer both exclusive and non-exclusive ticketing proposals going forward.
The existing DOJ consent decree will be extended for eight years with stronger oversight provisions.
One detail jumps out in how Live Nation makes money. Despite dominating the live events ecosystem, Live Nation’s profits remain surprisingly thin. The company generated $25.2 billion in revenue but only $0.7 billion in net income in FY25, a net margin of just 3%.
That’s because the bulk of the business is concert promotion, where most ticket revenue flows to artists and production costs. Critics argue the company’s market power lies less in massive margins and more in control of the ecosystem (promotion, venues, and ticketing all under one roof).
The biggest headline today is that Ticketmaster stays inside the empire.
Breaking up Live Nation’s ticketing and promotion businesses had been the core structural risk hanging over the stock since the lawsuit was filed in 2024.
However, the legal fight is far from over.
More than two dozen US states rejected the settlement and plan to continue pursuing the case in court, arguing that the agreement fails to address what they view as a monopoly over live events.
Live Nation has set aside $280 million to cover potential damages tied to those state claims.
For now, the outcome removes the most extreme scenario of a forced divestiture of Ticketmaster. But it leaves a lingering legal overhang as the state-led case moves forward.
Meta unveiled a roadmap for four new in-house AI chips this week: MTIA 300, 400, 450, and 500. The chips will roll out through 2027 and are designed to support everything from content ranking and recommendations to gen AI inference.
The bigger point is inference. Meta is increasingly designing chips not just for training models, but for running AI workloads efficiently at scale. This matters because AI is becoming a much larger cost center for Meta.
It also hints at a narrower focus. Earlier this month, reports said Meta had scrapped some of its most ambitious training-chip efforts, including Iris and Olympus, after design struggles. That makes this roadmap look less like a full challenge to NVIDIA and more like a focused attempt to optimize the workloads Meta knows best.
Meta is not doing this alone. The MTIA family is being co-developed with Broadcom, which gives Meta access to proven silicon expertise while accelerating its roadmap. Meta wants to hit a blistering 6-month release cadence to ensure its hardware doesn’t become obsolete before it even reaches the data center.
Despite this in-house push, Meta is still spending billions with NVIDIA and AMD. In fact, Meta just signed a massive $100 billion deal with AMD for 6 gigawatts of MI450 GPUs. Ultimately, the goal is not to replace third-party chips overnight, but to diversify suppliers, lower costs, and better optimize chips for its own workloads.
Every recommendation, every generated image, every chatbot response has to run somewhere. If Meta can lower inference costs across Facebook, Instagram, WhatsApp, and its ad stack, the savings add up fast.
There is still execution risk. Custom chips are expensive to design, take years to bring into production, and only really pay off at huge scale. Meta is betting that better bandwidth density can lower the cost of inference at scale.
Inference is often constrained less by raw compute than by how quickly data can move between memory and processors. By designing for this specific constraint, Meta claims that the MTIA 500 will deliver 27.6 TB/s of bandwidth, potentially outperforming even NVIDIA’s specialized Rubin chips for Meta’s internal workloads.
The biggest AI spenders increasingly want more control over their own infrastructure economics. After spending over $70 billion in 2025, Meta is guiding to $115–$135 billion in capital expenditures in 2026. It’s the third-largest infrastructure budget, only behind Amazon and Google.
Meta’s AI bill is getting so large that even small efficiency gains start to matter. Custom chips are becoming one of the clearest ways to protect margins as inference scales.
That’s it for today!
Happy investing!
Thanks to Fiscal.ai for being our official data partner. Create your own charts and pull key metrics from 50,000+ companies directly on Fiscal.ai. Save 15% with this link.
Disclosure: I own AMZN, AMD, AVGO, GOOG, LYV, META, and NVDA in App Economy Portfolio. I share my ratings (BUY, SELL, or HOLD) with App Economy Portfolio members.
Author's Note (Bertrand here 👋🏼): The views and opinions expressed in this newsletter are solely my own and should not be considered financial advice or any other organization's views.
2026-03-11 06:53:46
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Alphabet sold a $31.5 billion global bond deal in February to help fund its AI expansion. Amazon is now targeting at least $37 billion in a new bond sale tied to AI infrastructure.
Oracle, meanwhile, said it plans to raise $45 billion to $50 billion this year through a mix of debt and equity to expand cloud capacity.
What makes Oracle different is the balance-sheet starting point. Alphabet and Amazon are raising debt from a position of financial strength. Oracle is trying to finance its AI buildout while already carrying a reputation as the most leveraged among the major tech platforms.
New reports suggest Oracle is preparing thousands of job cuts and slowing hiring as the cost of that buildout mounts. The debate is now all about how much financial strain Oracle must absorb before that demand turns into durable returns.
Free cash flow flipped to negative $25 billion in the trailing 12 months (TTM), with $11 billion used in Q3 alone. What could possibly go wrong?
ORCL is trading over 50% below its September peak. The stock has always been central to Larry Ellison’s empire. Now it matters even more, because that equity is helping support the family’s massive Warner bet.
Let’s see what we learned this quarter.
Today at a glance:
☁️ Oracle: The Art of Leverage
🤖 Microsoft: Borrowing Anthropic’s Best Trick
☁️ Revenue growth accelerated (with a catch): Total revenue reached $17.2 billion, up 22% Y/Y. In constant currency, growth was just 18%, meaning some of the upside came from FX rather than from underlying demand.
📦 Backlog keeps climbing: RPO reached $553 billion, up 325% Y/Y and 6% sequentially. Management also said many new AI contracts require less Oracle funding because customers are prepaying or supplying GPUs directly.
⚡ OCI accelerated again: Oracle Cloud Infrastructure (OCI) revenue grew 84% Y/Y to $4.9 billion, up from 68% last quarter. Total cloud revenue rose 44% to $8.9 billion, while multicloud database revenue surged 531%.
💵 Guidance moved higher: Management reaffirmed FY26 revenue guidance of $67 billion and raised FY27 revenue guidance by $4 billion to $90 billion.
Income statement:
Revenue grew +22% Y/Y to $17.2 billion ($0.3 billion beat).
☁️ Cloud +44% Y/Y to $8.9 billion.
🌐 Software +3% Y/Y to $6.1 billion.
🖥️ Hardware +2% Y/Y to $0.7 billion.
💼 Services +12% Y/Y to $1.4 billion.
The shift to IaaS compressed gross margins to 65% (-6pp Y/Y).
Operating margin was 32% (+1pp Y/Y).
Cash flow:
Operating cash flow TTM was up 13% to $24 billion.
Free cash flow TTM was negative $25 billion and remains under immense pressure due to the CapEx ramp.
Management kept the FY26 capital expenditure outlook intact at $50 billion.
Balance sheet:
Net debt: $114 billion (over 4x net leverage based on $28 billion EBITDA TTM).
